Hi,

This is a follow-up question regarding non-linear modeling from my post last
month. Although I have received some useful input at that time, I am still
not able to replicate the results that I am getting with the Excel Solver.

I may have left out some details in my original post (below) which may be
pertinent to the question at hand. The original equation is of the form:

log(column1 + A) = C * column2 + B

Here are the constraints on the paramaters:

A >= -(min(column1))
B = max(log(column1 + A)) - max(column2) * B
C is the slope of the predicted log(column1 + A) values and the original
column2 values.

I would like to know how I could set the initial parameters and bounds on
parameters B and C, which are dependent on other parameter(s) and variables
while using PROC NLIN/PROC NLMIXED/PROC OPTMODEL?

Thank you again in advance.

Sid

On Thu, Nov 12, 2009 at 5:03 PM, Sid N <nsid31@gmail.com> wrote:

> Hi,
>
> I would like to find the maximum R^2 that can be attained between
> log(column1 + a) and (c * column2 + b) for the below dataset by changing
> the
> values for a, b and c. Previously, I have used the 'Solver' add-in in
> Excel.
>
> data have;
> input column1 column2;
> datalines;
> 30000 6000000
> 50000 10000000
> 65000 13000000
> 70000 13500000
> 76000 13525000
> 113000 13925000
> 115500 15925000
> 119500 16925000
> 121500 17425000
> 122500 17725000
> ;
> run;
>
> Based on what I have read from the SAS-L posts, I understand that PROC NLP
> can help me do the same in SAS. Can someone please assist me with using
> this
> procedure? Thank you for your time.
>
> Sid
>